1,721,200 research outputs found
1998-2003, five years of antepartum monitoring: what can we learn from fetal heart rate analysis?
No full textNonlinear analysis of Heart Rate Variability signal: physiological knowledge and diagnostic indications
No full textThe complex structure of the Heart Rate Variability signal (HRV) has been widely studied in order to identify the "complex" nature of its control mechanisms. By adopting methods based on the reconstruction of the HRV time series, in an embedding space, the Fractal Dimension and the Lyapunov Exponents can be computed. These estimations must be associated to a determinism test based on surrogate data, confirming that it is a deterministic instead of a linear correlation mechanism that controls the HRV dynamics. Results in 24 hours HRV series confirm that the structure generating the signal is neither linear nor stochastic. Furthermore, methods quantifying fractal and self-similar "monofractal" characteristics (1/fα spectrum, detrended fluctuation analysis, DFA) and a regularity statistic (approximate entropy, ApEn), allow characterizing the HRV signal and distinguishing pathological from
healthy subjects. Results in the HRV signal analysis confirm the presence of a nonlinear deterministic structure in time series. Moreover, nonlinear parameters can be used to separate normal from pathological subjects. Application examples are shown concerning cardiovascular pathologies and fetal heart rate analysis
Studio di modelli di caos deterministico con applicazione al sistema cardiovascolare
No full textTesi di Dottorato di Ricerca in Bioingegneria, VII ciclo, Politecnico di Milano
Nonlinear dynamic approach in the analysis of cardiovascular variability signals in normal and pathological subjects
No full textWe study the complex, long-term dynamics underlying the Heart Rate variability (HRV) signal through the chaotic deterministic approach. We calculate the geometric fractal dimension of the system space state, the Entropy, the maximum positive λ1 Lyapunov Exponent and the self similarity Hurst exponent in HRV. These parameters estimate the properties of a nonlinear dynamic system. Data were also submitted to a determinism test. Series of about 20,000 R-R intervals were selected in 24h Holter recordings 9 Normal subjects, 6 hypertensive, 11 severe heart failure and 7 orthotopic transplanted in day and night epochs. Correlation dimension (D2), Entropy (K) and H self similar parameter show a significant decrease passing from normal to pathological subjects. The trend of various and different parameters suggests nonlinear dynamic in the generation mechanism of HRV signal. Interpretation of results seems consistent with a complex cardiovascular pathophysiology that shows, in the long-term regulation, nonlinear properties
Long term effects of AP5 and TTX administration on neuronal network evaluated on in vitro MEA cultivations
No full textAnalysis of fetal heart rate variability signal to separate distressed iugr fetuses from SGA fetuses
No full textEstimation of nonlinear parameters in variability time series: determinism tests and noise reduction methods
No full textEvaluation of a blind method for the estimation of Hurst''s exponent in time series
Full text linkPublication in the conference proceedings of EUSIPCO, Florence, Italy, 200
Evaluation of Lempel Ziv Complexity index for the analysis of Heart Rate Variability signal
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